Systems and methods for dynamic control of enteral feeding according to energy expenditure

ABSTRACT

A computer-implemented method of adjusting enteral feeding of a patient by an enteral feeding controller, comprising: computing an estimate of energy expenditure of the patient based on oxygen measurements and carbon dioxide measurements of the patient, computing a target composition and target feeding rate for the enteral feeding according to the computed estimate of energy expenditure, when the target composition and target feeding rate differ from a current enteral feeding composition and feeding rate by a requirement, generating instructions for adjustment, by an enteral feeding controller, of the rate of delivery of the enteral feeding according to the target composition, wherein the receiving the oxygen measurement, receiving the carbon dioxide measurement, and computing the estimate of energy expenditure are performing iteratively for every first time interval, and the generating instructions for adjustment are performed for a second time interval that is larger than the first time interval.

RELATED APPLICATIONS

This application is a continuation of U.S. patent application Ser. No.17/156,683 filed on Jan. 25, 2021, which is a continuation of U.S.patent application Ser. No. 16/500,141 filed on Oct. 2, 2019, now U.S.Pat. No. 10,898,413, which is a National Phase of PCT Patent ApplicationNo. PCT/IL2017/051271 having International Filing Date of Nov. 21, 2017,which claims the benefit of priority under 35 USC § 119(e) of U.S.Provisional Patent Application No. 62/480,473 filed on Apr. 2, 2017. Thecontents of the above applications are all incorporated by reference asif fully set forth herein in their entirety.

FIELD AND BACKGROUND OF THE INVENTION

The present invention, in some embodiments thereof, relates to enteralfeeding systems and, more specifically, but not exclusively, systems andmethods for control of enteral feeding.

Patients requiring enteral feeding (i.e., feeding via a tube insertedinto the stomach) include, for example, babies, patients in theintensive care unit (ICU) which might be sedated and/or intubated, andpatients otherwise unable to swallow or ingest food in the normalmanner. The tube is inserted into the stomach (or duodenum, or jejunum,or other locations in the digestive track) via the nose, the mouth, or asurgically created opening. Recent research and practice indicated thatcorrect patient enteral feeding is a crucial element in patient survivalrate and recovery. Unfortunately in many cases the feed rate andcomposition is carried out when the patient enters the unit and updatesare rare if at all. Systems and methods for improving patient enteralfeeding are long sought after.

SUMMARY OF THE INVENTION

According to a first aspect, a computer-implemented method of adjustingenteral feeding of a patient by an enteral feeding controller,comprises: receiving carbon dioxide measurements outputted by a carbondioxide sensor that senses at least one of inspiration and expiration ofthe patient, receiving an oxygen measurement outputted by an oxygensensor that senses at least one of inspiration and expiration of thepatient, computing an estimate of energy expenditure of the patientbased on the oxygen measurement and the carbon dioxide measurement,computing a target composition and target feeding rate for the enteralfeeding according to the computed estimate of energy expenditure, whenthe target composition and target feeding rate differ from a currententeral feeding composition and feeding rate by a requirement,generating instructions for adjustment, by an enteral feedingcontroller, of the rate of delivery of the enteral feeding according tothe target composition, wherein the receiving the oxygen measurement,receiving the carbon dioxide measurement, and computing the estimate ofenergy expenditure are performing iteratively for every first timeinterval, and the generating instructions for adjustment are performedfor a second time interval that is larger than the first time interval.

According to a second aspect, a system for adjusting enteral feeding ofa patient by an enteral feeding controller, comprises: a non-transitorymemory having stored there a code for execution by at least one hardwareprocessor of a computing system, the code comprising: code for receivingcarbon dioxide measurements outputted by a carbon dioxide sensor thatsenses at least one of inspiration and expiration of the patient, codefor receiving an oxygen measurement outputted by an oxygen sensor thatsenses at least one of inspiration and expiration of the patient, codefor computing an estimate of energy expenditure of the patient based onthe oxygen measurement and the carbon dioxide measurement, code forcomputing a target composition and target feeding rate for the enteralfeeding according to the computed estimate of energy expenditure, codefor when the target composition and target feeding rate differ from acurrent enteral feeding composition and feeding rate by a requirement,generating instructions for adjustment, by an enteral feedingcontroller, of the rate of delivery of the enteral feeding according tothe target composition, wherein the receiving the oxygen measurement,receiving the carbon dioxide measurement, and computing the estimate ofenergy expenditure are performing iteratively for every first timeinterval, and the generating instructions for adjustment are performedfor a second time interval that is larger than the first time interval.

According to a third aspect, a computer program product for adjustingenteral feeding of a patient by an enteral feeding controller,comprises: a non-transitory memory having stored there a code forexecution by at least one hardware processor of a computing system, thecode comprising: instructions for receiving carbon dioxide measurementsoutputted by a carbon dioxide sensor that senses at least one ofinspiration and expiration of the patient, instructions for receiving anoxygen measurement outputted by an oxygen sensor that senses at leastone of inspiration and expiration of the patient, instructions forcomputing an estimate of energy expenditure of the patient based on theoxygen measurement and the carbon dioxide measurement, instructions forcomputing a target composition and target feeding rate for the enteralfeeding according to the computed estimate of energy expenditure,instructions for when the target composition and target feeding ratediffer from a current enteral feeding composition and feeding rate by arequirement, generating instructions for adjustment, by an enteralfeeding controller, of the rate of delivery of the enteral feedingaccording to the target composition, wherein the receiving the oxygenmeasurement, receiving the carbon dioxide measurement, and computing theestimate of energy expenditure are performing iteratively for everyfirst time interval, and the generating instructions for adjustment areperformed for a second time interval that is larger than the first timeinterval.

According to a fourth aspect, a computer-implemented method of adjustingenteral feeding of a patient by an enteral feeding controller,comprises: receiving a carbon dioxide measurement outputted by a carbondioxide sensor that senses inspiration and expiration of the patient,receiving an oxygen measurement outputted by an oxygen sensor thatsenses inspiration and expiration of the patient, computing an estimateof energy expenditure of the patient based on the oxygen measurement andthe carbon dioxide measurement, computing a target composition for theenteral feeding according to the computed estimate of energyexpenditure, computing an amount of supplemental protein to meet enteralfeeding requirements of the patient based on the computed energyexpenditure, the amount of supplemental protein computed based on thetarget composition in view of available formulation stored in a databasestoring records of different compositions of enteral feedingformulation, and generating instructions for adjustment, by an enteralfeeding controller, of the rate of delivery of the amount ofsupplemental protein and the target composition, wherein the receivingthe oxygen measurement, receiving the carbon dioxide measurement, andcomputing the estimate of energy expenditure are performing iterativelyfor every first time interval, and the generating instructions foradjustment are performed for a second time interval that is larger thanthe first time interval.

The systems, methods, apparatus, and/or code instructions describedherein relate to the technical problem of control of enteral feeding ofa patient. Design and/or selection of an appropriate enteral feedingregime, which includes the feeding rate (e.g., calories per unit oftime) and/or composition of the enteral feeding (e.g., mix ofcarbohydrates, protein, fat and/or other nutrients) affects patientsurvival and recovery.

According to standard practice (e.g., when the patient enters theintensive care unit (ICU)) a feeding plan (e.g., formulation, rate,pattern of delivery) is manually assigned, for example, by a healthcareprovider and/or nutritionist currently calculating nutritional goalaccording to Harris Benedict formula or alike (which is generally notaccurate and/or performed only one time for the patient) and notaccording to dynamic- and changing nutritional goal as patient statuscontinuously changes. The feeding plan is selected according to thespecific situation of the patient, according to specification(s) of thevariations of feedings available from different vendors, and thecurrently stocked supply. The feeding plan is manually designed based ondietician and/or nutritionist knowhow and/or known recommended formulas,team leader experience (e.g., head of ICU), and/or patient specificrequirement as prescribed by the current attending physical. The manualmethod, which is based on subjective inputs from one or more people,results in sub-optimal planning for the specific patient that does notprecisely match the patient's current metabolism.

In contrast to the standard manual practice, the systems, methods,apparatus, and/or code instructions described herein without the needfor a “man in the loop” dynamically determine objectively the patientcondition in terms of energy expenditure, and dynamically adjust theenteral feeding accordingly.

The systems, methods, apparatus, and/or code instructions describedherein may further relate to the technical problem of adjusting patiententeral feeding according to dynamic patient conditions. For example, inthe ICU, the patient condition may change rapidly, and many variationsmay be experienced. For example, as the patient recovers, undergoeschanges in treatments, and experiences new infections and new medicalconditions. The current practice of manual methods, which are based onmanual calculations of the most suitable enteral feeding regime at acertain point in time, are unable to adequately adapt to rapidlychanging patient conditions. For example, continuous checking thepatient, analyzing the patient condition, replacing different feedings,and updating of the feeding regiment are impractical and cannot bemanually performed to keep up with the changing condition of thepatient.

When the patient feeding is manually determined and manually performed,the determination of how to feed the patient is based on outdated datawhich do not reflect the actual current state of the patient. Therefore,the manually determined feeding plan is not suitable for the currentstate of the patient. In contrast, the systems, methods, and/or codeinstructions described herein obtain an accurate current state of thepatient, and dynamically select and/or adjust the feeding regimen (e.g.,composition, rate) for the patient based on the current state of thepatient. The feeding regimen is quickly adjusted to reflect changes inthe current state of the patient, which cannot be performed by manualmethods that are based on outdated states of the patient and not thecurrent state of the patient.

Moreover, healthcare providers are unable to continuously monitorpatient caloric consumption, which may lead to sub-optimal feeding ofthe patient, for example, underfeeding of the patient which may lead toinadequate caloric and/or protein and or nutrition intake with adverseeffects on recovery and/or survival, and/or overfeeding (it is notedthat overfeeding may be an indication of poor stomach pyloric dischargeor other gastric blockage that require special treatment) of the patientwhich may lead to reflux and associated risks thereof (e.g., aspirationpneumonia).

The systems, methods, apparatus, and/or code instructions describedherein do not simply perform automation of a manual procedure, butperform additional automated features which cannot be performed manuallyby a human using pencil and/or paper. For example, combination of foodsources may be controlled each at a respective rate, for example, a highprotein food source and a standard food source. In another example, thecomputations are performed in real-time (i.e., over short intervals)based on sensors measuring oxygen, carbon dioxide, and/or nitrogen flowsof the patient, which cannot be performed manually. In yet anotherexample, the target composition and target feeding rate are computedaccording to the computed energy expenditure and evaluated to determinewhether a significant change has occurred from the current feeding.Instructions to adjust the feeding controller are automaticallygenerated when the significant change occurs, to change the compositionand/or feeding rate. The process is iterated at short time intervals toquickly identify changes in the energy expenditure of the patient andadjust feeding accordingly, which cannot be performed manually. In yetanother example, the feeding is adjusted in real-time to prevent orreduce reflux based on estimated GRV. In another example, a predictionof future feeding needs is made based on historical measurements offeeding performance.

The GUI associated with the systems, apparatus, methods and/or codeinstructions described herein generates a new user experience, one thatis different than manually trying to select feeding formulas and selectthe feeding rate. For example, the GUI guides the user through theprocess of selecting the feeding formulas and the feeding rate, asdescribed herein. The GUI visually presents different suitable andavailable feeding formulas for the user to pick from. The GUI guides theuser to select supplemental protein from suitable and available feedingformula. The GUI presents to the user suitable options based on theautomatically computed resting energy expenditure of the patient, whichaids the user in making correct feeding selections. The GUI may presenta graphical representation of selected intermittent feeding parameters,to help visualize how the feeding will take placing during the upcomingtime interval.

The systems, methods, and/or code instructions described herein do notsimply display information using a GUI. The systems, methods, and/orcode instructions described herein may be based on a specific,structured GUI, which is paired with a prescribed functionality directlyrelated to the GUI's structure that is addressed to and resolves thespecifically identified technical problem.

When the features related to by the systems, methods, apparatus, and/orcode instructions described herein are taken as a whole, the combinationof the features amounts to significantly more than a simple mathematicalcalculation of computing the estimated energy expenditure rate (e.g.,the resting energy expenditure rate). The systems, methods, apparatus,and/or code instructions described herein do not merely relate tomathematical computations (e.g., equations), but relate to theparticular data collected, stored, and the way the data is collected bysensors, and how instructions for adjustment of the enteral feedingdevice (e.g., pump, valve) are automatically generated.

In a further implementation form of the first, second, and thirdaspects, the method further comprises and/or the system further includescode for and/or the computer program product includes additionalinstructions for performing an analysis of real-time patient vial signmeasurements collected from an electronic medical record of the patientto determine whether the patient is at rest, wherein the energyexpenditure of the patient is computed when the patient is determined tobe at rest.

In a further implementation form of the first, second, and thirdaspects, the second time interval is about 20 minutes or less.

In a further implementation form of the first, second, and thirdaspects, the instructions for adjustment include a first feedinginterval associated with the rate of delivery of the enteral feeding,and second non-feeding interval during which no enteral feeding isdelivered, wherein the first and second intervals are iterated.

In a further implementation form of the first, second, and thirdaspects, the target feeding rate is calculated based on carbon dioxidemeasurements alone when oxygen measurements are not available, and anestimated value for a respiratory quotient (RQ).

In a further implementation form of the first, second, and thirdaspects, the method further comprises and/or the system further includescode for and/or the computer program product includes additionalinstructions for receiving a nitrogen measurement outputted by anitrogen sensor associated with a urine output collection device thatcollects urine outputted by the patient, and wherein the estimate ofenergy expenditure is further computed according to the nitrogenmeasurement.

In a further implementation form of the first, second, and thirdaspects, the method further comprises and/or the system further includescode for and/or the computer program product includes additionalinstructions for computing an amount of supplemental protein to meetenteral feeding requirements of the patient based on the computed energyexpenditure, the amount of supplemental protein computed based on thetarget composition in view of available formulation stored in a databasestoring records of different compositions of enteral feedingformulation, wherein the supplemental protein when added to a selectedavailable formulation does not significantly affect a computed caloricand/or volumetric feed rate of the available formulation to trigger are-computation of the feeding rate of the available formulation.

In a further implementation form of the first, second, and thirdaspects, the method further comprises and/or the system further includescode for and/or the computer program product includes additionalinstructions for matching the computed target composition to at leastone record of an available formulation stored in a database storingrecords of different compositions of enteral feeding formulation,wherein the instructions for adjustment are generated based on thematched at least one record.

In a further implementation form of the first, second, and thirdaspects, the method further comprises and/or the system further includescode for and/or the computer program product includes additionalinstructions for, when at least one record is matched to the targetcomposition, presenting on a display the at least one record, andreceiving via a user interface a selection of a certain record from thepresented at least one record, wherein the instructions for adjustmentare generated according to the selected certain record.

In a further implementation form of the first, second, and thirdaspects, the method further comprises and/or the system further includescode for and/or the computer program product includes additionalinstructions for computing a score indicative of similarity between eachrespective record and the target composition, and presenting the scorein association with each respective record.

In a further implementation form of the first, second, and thirdaspects, the method further comprises and/or the system further includescode for and/or the computer program product includes additionalinstructions for when no records are matched to the target composition,independently matching a plurality of component sets of the targetcomposition to respective a plurality of records, wherein each of aplurality of instructions for adjustment is generated according to arespective matched record of the plurality of records.

In a further implementation form of the first, second, and thirdaspects, a first set of components denotes arbitrary components matchedto a first formulation, and a second set of components denotes a pureprotein component matched to a second formulation, wherein a first setof instructions is generated for enteral feeding of the firstformulation at a first rate, and a second set of instructions isgenerated for enteral feeding of the second formulation at a secondrate.

In a further implementation form of the first, second, and thirdaspects, the target composition is computed based on an aggregation ofdata collected from a plurality of sampled individuals, wherein thetarget composition is computed according to a likelihood of obtaining apositive outcome.

In a further implementation form of the first, second, and thirdaspects, the generated instructions include a first set of instructionsfor delivery of a first enteral feeding formulation at a first rate, anda second set of instructions for delivery of a second enteral feedingformulation at a second rate, wherein the first set of instructions andthe second set of instructions control a feed selecting mechanism thatselects between a first tube that delivers the first enteral feedingformulation at the first rate and a second tube that delivers the secondenteral feeding formulation at the second rate, wherein the first tubeand the second tube connect into a combined tube that provides enteralfeeding of the patient.

In a further implementation form of the first, second, and thirdaspects, the estimate of energy expenditure comprises an estimate ofcaloric expenditure of the patient, and wherein the enteral feedingcontroller dynamically adjusts the feeding rate to deliver calories tothe patient according to the estimate of caloric expenditure.

In a further implementation form of the first, second, and thirdaspects, the estimate of energy expenditure is dynamically computed as arate of energy expenditure for a predefined time duration during whichthe oxygen and carbon dioxide measurements are obtained, and wherein thefeeding rate provided by the enteral feeding controller is dynamicallyadjusted to match the rate of energy expenditure within a tolerancerequirement.

In a further implementation form of the first, second, and thirdaspects, the generated instructions define a feeding rate set below areflux feeding level estimated to trigger reflux of the enteral feedingby the patient.

In a further implementation form of the first, second, and thirdaspects, the reflux feeding level is computed according to the net foodportion of an estimated gastro residual volume (GRV), computed based onweight, volume, and specific gravity of the enteral feeding formulationdelivered by the enteral feeding controller.

In a further implementation form of the first, second, and thirdaspects, the reflux feeding level is further computed according tohistorical feeding performance of the target individual.

In a further implementation form of the first, second, and thirdaspects, the target composition and target feeding rate include a volumeof water.

In a further implementation form of the first, second, and thirdaspects, the method further comprises and/or the system further includescode for and/or the computer program product includes additionalinstructions for presenting on a display within a graphical userinterface (GUI), at least one of: current computed energy expenditure, atrend based on history of the computed energy expenditure, currentfeeding rate delivered by the enteral feeding controller, and computedcomposition of the enteral feeding being delivered by the enteralfeeding controller.

In a further implementation form of the first, second, and thirdaspects, the estimate of energy expenditure is computed based on a Weiror corresponding equations, and based on metabolic rate estimated fromoxygen consumption computed based on the oxygen measurement and carbondioxide production computed based on the carbon dioxide measurement.

In a further implementation form of the first, second, and thirdaspects, the method further comprises and/or the system further includescode for and/or the computer program product includes additionalinstructions for setting an initial feeding rate by the enteral feedingcontroller independently of the oxygen and carbon dioxide measurement,computing an mismatch between the computed estimate of energyexpenditure and the initial feeding rate state, wherein the generatedinstructions include instructions for adjusting the initial feeding rateof the enteral feeding controller according to the computed mismatch.

In a further implementation form of the first, second, and thirdaspects, the estimate of energy expenditure comprises a prediction offuture energy expenditure computed by machine learning code instructionstrained according to previously observed patterns.

In a further implementation form of the first, second, and thirdaspects, the rate of delivery of the enteral feeding is further computedaccording to historical feeding performance of the patient indications.

In a further implementation form of the first, second, and thirdaspects, the carbon dioxide sensor is mounted on a ventilation tubeventilating the patient.

In a further implementation form of the fourth aspect, the amount ofsupplemental protein is computed for adding each of the availableformulations for reaching about 100% of protein requirements of thecomputed target composition for the enteral feeding.

In a further implementation form of the fourth aspect, the methodfurther comprises performing an analysis of real-time patient vial signmeasurements collected from an electronic medical record of the patientto determine whether the patient is at rest, wherein the energyexpenditure of the patient is computed when the patient is determined tobe at rest.

In a further implementation form of the fourth aspect, the methodfurther comprises setting a clinical state of the patient, wherein thetarget feeding composition is computed according to the clinical stateof the patient.

In a further implementation form of the fourth aspect, the clinicalstate of the patient is selected from the group comprising: maintenance,stressed/MICU, trauma/general surgery, trauma/ICU, burn(s), cancer,obesity (e.g., body mass index (BMI) >29.9).

In a further implementation form of the fourth aspect, the methodfurther comprises setting a weight of the patient, wherein the targetfeeding composition is computed according to the weight of the patient.

In a further implementation form of the fourth aspect, the methodfurther comprises presenting on a display within a graphical userinterface (GUI), an indication of a computed state of whether thepatient is rested or un-rested, when the patient is determined as restedpresenting an indication of the computed estimate of energy expenditurewithin the GUI, receiving via the GUI a setting of a patient weight, anda selection from a plurality of icons each denoting a respectiveclinical state of the patient, receiving via the GUI a selection of oneicon indicative of one of the available formulation from a plurality ofavailable formulations stored in the database and presented within theGUI based on respective icons, receiving via the GUI a selection of oneicon indicative of one available supplemental protein formulationsatisfying the amount of supplemental protein from a plurality ofavailable formulations satisfying the amount of supplemental proteinstored in a database storing records of different compositions ofsupplemental protein, and presented within the GUI based on respectiveicons, wherein the instructions for adjustment are generated accordingto the selections received via the GUI.

In a further implementation form of the fourth aspect, the methodfurther comprises receiving, via the GUI, a selection of: an iconindicative of intermittent feeding, an icon indicative of a number ofhours of a frequency of the intermittent feeding, an icon indicative ofa number of hours of a duration of the intermittent frequency, an iconindicative of a number of minutes for tapering up each feeding interval,and an icon indicative of a number of minutes for tapering down eachfeeding interval.

In a further implementation form of the fourth aspect, the methodfurther comprises presenting within the GUI, a graphical timelineindicative of feeding intervals during an upcoming feeding period,wherein solid portions of a first color of the timeline are indicativeof time intervals during which entering feeding is taking place, thelength of each solid portion of the first color is according to theselected duration, solid portions of a second color of the timeline areindicative of time intervals during which enteral feeding is stopped,the length of each solid portion of the second color is according to theselected frequency less the selected duration, mixed portions thatrepresents a mixture of the first and second colors located before eachsolid portion of the first color are indicative of taper up and have alength according to the selected taper up time, and mixed portionslocated after each solid portion of the first color are indicative oftaper down and have a length according to the selected taper down time.

Unless otherwise defined, all technical and/or scientific terms usedherein have the same meaning as commonly understood by one of ordinaryskill in the art to which the invention pertains. Although methods andmaterials similar or equivalent to those described herein can be used inthe practice or testing of embodiments of the invention, exemplarymethods and/or materials are described below. In case of conflict, thepatent specification, including definitions, will control. In addition,the materials, methods, and examples are illustrative only and are notintended to be necessarily limiting.

BRIEF DESCRIPTION OF THE SEVERAL VIEWS OF THE DRAWINGS

Some embodiments of the invention are herein described, by way ofexample only, with reference to the accompanying drawings. With specificreference now to the drawings in detail, it is stressed that theparticulars shown are by way of example and for purposes of illustrativediscussion of embodiments of the invention. In this regard, thedescription taken with the drawings makes apparent to those skilled inthe art how embodiments of the invention may be practiced.

In the drawings:

FIG. 1A is a flowchart of a method of dynamically adjusting an enteralfeeding device for controlling the enteral feeding rate according to anestimate of energy expenditure computed based on output of sensors, inaccordance with some embodiments of the present invention;

FIG. 1B is a flowchart of a method of dynamically adjusting an enteralfeeding device for controlling the feed rate according to an estimate ofthe energy expenditure computed based on output of sensors andsupplementing the feed formula with extra protein, in accordance withsome embodiments of the present invention;

FIG. 2 is a schematic of components of a system for estimating energyexpenditure based on output of sensors, and generating instructions foradjustment of the enteral feeding rate provided by an enteral feedingcontroller according to the estimated energy expenditure, in accordancewith some embodiments of the present invention;

FIG. 3 is a schematic depicting an example of a record of a certainenteral feeding product formulation, in accordance with some embodimentsof the present invention;

FIG. 4 is a schematic of an exemplary implementation of the enteralfeeding device for independent control of the rate of delivery of twocomponents of the enteral feeding, in accordance with some embodimentsof the present invention;

FIG. 5 is a dataflow diagram of dynamic adjustment of an enteral feedingrate by an enteral feeding controller according to an estimated energyexpenditure computed based on output of sensor(s), in accordance withsome embodiments of the present invention; and

FIGS. 6A-6J include a sequence of exemplary GUI images depicting anexemplary flow for implementing the method of dynamically adjusting anenteral feeding device for controlling the feed rate according to anestimate of the energy expenditure computed based on output of sensorsand supplementing the feed formula with extra protein, in accordancewith some embodiments of the present invention.

DESCRIPTION OF SPECIFIC EMBODIMENTS OF THE INVENTION

The present invention, in some embodiments thereof, relates to enteralfeeding systems and, more specifically, but not exclusively, systems andmethods for control of enteral feeding.

An aspect of some embodiments of the present invention relates tosystems, an apparatus, methods, and/or code instructions (stored in adata storage device, executable by one or more hardware processors) foradjusting the rate of enteral feeding and optionally selecting the typeand/or brand of the feeding to be administered for a patient being tubefed by an enteral feeding controller. The rate is adjusted according toa computed estimate of energy expenditure of the patient whilemaintaining percussions against over feeding that may result undesiredreflux. The estimated energy expenditure is computed based on output ofone or more sensors such as a carbon dioxide sensor, flow sensor andoptionally adding an oxygen sensor that measure inspiration and/orexpiration of the patient (e.g., associated with a ventilation deviceand/or installed), and optionally based on a nitrogen sensor associatedwith a urine output device or any other means that detects the energyexpenditure of the patient. The sensor measurements may be performed inreal-time, for example, continuously (and/or substantially continuouslywhen digital signals are outputted at a certain frequency resemblingcontinuous monitoring), or over time intervals for example less thanabout 5-30 minutes. The estimated energy expenditure may be computed inreal-time (i.e., closely following the received sensor measurements) andthe rate of enteral feeding adjusted accordingly, in real-time. Thefeeding rate of the enteral feeding provided to the patient isdynamically adjusted according to the dynamic energy consumption of thepatient. As the patient's condition changes (e.g., due to stress,recovery, movement, medication administration, infection), the energyconsumption of the patient changes, and is met by the dynamic control ofthe enteral feeding device.

Optionally, a target composition of the enteral feeding is computedaccording to the computed estimated energy expenditure. The targetcomposition and/or target feeding rate may be computed according to thenutritional goal of the patient. The computed target composition may bematched by one or more formulations that are actually available used asan initial setting and/or, for example having records stored in adatabase. When the match is not exact, but represents a similarformulation, the user may select one of the matched records, forexample, the most similar formulation that is available in stock. Whenno matching records are found (i.e., according to the similarityrequirement), subsets of components of the target composition may beindependently matched as close as possible to formulation required. Adifferent feeding rate may be computed for each matched formulation. Amechanism of the enteral feeding controller controls delivery of eachmatched formulation according to the respective computed rate.

Optionally, when the target composition and target feeding rate differfrom a current enteral feeding composition and feeding rate by amanually defined and/or automatically computed requirement (e.g.,percent difference, absolute difference, for example, about 10%) theinstructions are generated for adjustment of the rate of delivery of theenteral feeding according to the target composition.

The receiving of the oxygen and/or carbon dioxide measurements andcomputing of the estimate of energy expenditure are performingiteratively for every first time interval, for example, every 1 minute,5 minutes, 10 minutes, or other values. The instructions for adjustmentare generated (when the requirement is met) for a second time intervalthat is larger than the first time interval, for example, 30 minutes, 60minutes, 120 minutes, or other values. The second interval may includemultiple time intervals, for example, the instructions are generatedbased on the previous six first time intervals of five minutes each(e.g., 6×5 minutes=30 minutes. Alternatively or additionally,instructions are generated every second interval, for example, newinstructions are generated every 30 minutes (when such new instructionsare triggered by significant difference in the energy expenditure of thepatient according to the requirement). Effectively, the patient may bemonitored for computation of the energy expenditure continuously orclose to continuously, with changes to the feeding occurringperiodically.

An aspect of some embodiments of the present invention relates tosystems, an apparatus, methods, and/or code instructions (stored in adata storage device, executable by one or more hardware processors) foradjusting the rate of enteral feeding for including a protein supplementfor obtaining about 100% of a computed target feeding rate of thepatient. When the target composition of the enteral feeding is computed,the amount of supplemental protein for adding to available feedingformulations (stored in a database storing records of differentformulations) is computed accosting to the target composition. Theinstructions are generated according to a selection of the availablefeeding formulations and the amount of supplemental protein (which maybe selected according to available supplemental protein formulations).

Inventors observed that in many cases, the calories and proteins ofcommercially available feeding formulations do not directly match withinthe tolerance the computed REE. The most common case is lack ofsufficient protein within the commercially available feedingformulations to meet patient demands based on REE. When caloriescomputed according to REE are met by the selected feeding formulations,in many cases the protein requirements are not fully met. For example,the commercially available feeding formulation may include 100% of thecalories according to the REE, and about 80% of the determined proteinrequirements.

Optionally, the estimated of the energy expenditure for computation ofthe target composition is performed when the patient is resting. Ananalysis of real-time patient vital sign measurements collected from anelectronic medical record of the patient may be performed to determinewhether the patient is at rest.

The systems, methods, apparatus, and/or code instructions describedherein relate to the technical problem of control of enteral feeding ofa patient. Design and/or selection of an appropriate enteral feedingregime, which includes the feeding rate (e.g., calories per unit oftime) and/or composition of the enteral feeding (e.g., mix ofcarbohydrates, protein, fat and/or other nutrients) affects patientsurvival and recovery.

According to standard practice (e.g., when the patient enters theintensive care unit (ICU)) a feeding plan (e.g., formulation, rate,pattern of delivery) is manually assigned, for example, by a healthcareprovider and/or nutritionist currently calculating nutritional goalaccording to Harris Benedict formula or alike (which is generally notaccurate and/or performed only one time for the patient) and notaccording to dynamic- and changing nutritional goal as patient statuscontinuously changes. The feeding plan is selected according to thespecific situation of the patient, according to specification(s) of thevariations of feedings available from different vendors, and thecurrently stocked supply. The feeding plan is manually designed based ondietician and/or nutritionist knowhow and/or known recommended formulas,team leader experience (e.g., head of ICU), and/or patient specificrequirement as prescribed by the current attending physical. The manualmethod, which is based on subjective inputs from one or more people,results in sub-optimal planning for the specific patient that does notprecisely match the patient's current metabolism.

In contrast to the standard manual practice, the systems, methods,apparatus, and/or code instructions described herein without the needfor a “man in the loop” dynamically determine objectively the patientcondition in terms of energy expenditure, and dynamically adjust theenteral feeding accordingly.

The systems, methods, apparatus, and/or code instructions describedherein may further relate to the technical problem of adjusting patiententeral feeding according to dynamic patient conditions. For example, inthe ICU, the patient condition may change rapidly, and many variationsmay be experienced. For example, as the patient recovers, undergoeschanges in treatments, and experiences new infections and new medicalconditions. The current practice of manual methods, which are based onmanual calculations of the most suitable enteral feeding regime at acertain point in time, are unable to adequately adapt to rapidlychanging patient conditions. For example, continuous checking thepatient, analyzing the patient condition, replacing different feedings,and updating of the feeding regiment are impractical and cannot bemanually performed to keep up with the changing condition of thepatient.

When the patient feeding is manually determined and manually performed,the determination of how to feed the patient is based on outdated datawhich do not reflect the actual current state of the patient. Therefore,the manually determined feeding plan is not suitable for the currentstate of the patient. In contrast, the systems, methods, and/or codeinstructions described herein obtain an accurate current state of thepatient, and dynamically select and/or adjust the feeding regimen (e.g.,composition, rate) for the patient based on the current state of thepatient. The feeding regimen is quickly adjusted to reflect changes inthe current state of the patient, which cannot be performed by manualmethods that are based on outdated states of the patient and not thecurrent state of the patient.

Moreover, healthcare providers are unable to continuously monitorpatient caloric consumption, which may lead to sub-optimal feeding ofthe patient, for example, underfeeding of the patient which may lead toinadequate caloric and/or protein and or nutrition intake with adverseeffects on recovery and/or survival, and/or overfeeding (it is notedthat overfeeding may be an indication of poor stomach pyloric dischargeor other gastric blockage that require special treatment) of the patientwhich may lead to reflux and associated risks thereof (e.g., aspirationpneumonia).

The systems, methods, apparatus, and/or code instructions describedherein do not simply perform automation of a manual procedure, butperform additional automated features which cannot be performed manuallyby a human using pencil and/or paper. For example, combination of foodsources may be controlled each at a respective rate, for example, a highprotein food source and a standard food source. In another example, thecomputations are performed in real-time (i.e., over short intervals)based on sensors measuring oxygen, carbon dioxide, and/or nitrogen flowsof the patient, which cannot be performed manually. In yet anotherexample, the target composition and target feeding rate are computedaccording to the computed energy expenditure and evaluated to determinewhether a significant change has occurred from the current feeding.Instructions to adjust the feeding controller are automaticallygenerated when the significant change occurs, to change the compositionand/or feeding rate. The process is iterated at short time intervals toquickly identify changes in the energy expenditure of the patient andadjust feeding accordingly, which cannot be performed manually. In yetanother example, the feeding is adjusted in real-time to prevent orreduce reflux based on estimated GRV. In another example, a predictionof future feeding needs is made based on historical measurements offeeding performance.

The GUI associated with the systems, apparatus, methods and/or codeinstructions described herein generates a new user experience, one thatis different than manually trying to select feeding formulas and selectthe feeding rate. For example, the GUI guides the user through theprocess of selecting the feeding formulas and the feeding rate, asdescribed herein. The GUI visually presents different suitable andavailable feeding formulas for the user to pick from. The GUI guides theuser to select supplemental protein from suitable and available feedingformula. The GUI presents to the user suitable options based on theautomatically computed resting energy expenditure of the patient, whichaids the user in making correct feeding selections. The GUI may presenta graphical representation of selected intermittent feeding parameters,to help visualize how the feeding will take placing during the upcomingtime interval.

The systems, methods, and/or code instructions described herein do notsimply display information using a GUI. The systems, methods, and/orcode instructions described herein may be based on a specific,structured GUI, which is paired with a prescribed functionality directlyrelated to the GUI's structure that is addressed to and resolves thespecifically identified technical problem.

When the features related to by the systems, methods, apparatus, and/orcode instructions described herein are taken as a whole, the combinationof the features amounts to significantly more than a simple mathematicalcalculation of computing the estimated energy expenditure rate (e.g.,the resting energy expenditure rate). The systems, methods, apparatus,and/or code instructions described herein do not merely relate tomathematical computations (e.g., equations), but relate to theparticular data collected, stored, and the way the data is collected bysensors, and how instructions for adjustment of the enteral feedingdevice (e.g., pump, valve) are automatically generated.

The systems, methods, apparatus, and/or code instructions describedherein improve an underlying technical process within the technicalfield of enteral feeding systems, in particular within the field ofautomated control of patient enteral feeding.

The systems, methods, apparatus, and/or code instructions describedherein provide a unique, particular, and advanced technique ofdynamically determining the energy expenditure of the enteral fedpatient, and generating instructions for dynamically adjusting anenteral feeding device (e.g., pump, valve) delivering the enteralfeeding according to the determined energy expenditure, optionally tomatch (or minimize the difference, for example, within a tolerance) theenteral feeding to the energy expenditure.

The systems, methods, apparatus, and/or code instructions describedherein are tied to physical real-life components, for example, one ormore of: sensor(s) that measure oxygen, carbon dioxide, and nitrogen,computational hardware (e.g., hardware processor(s), physical memorydevice) that analyzes the sensor output, and an enteral feeding devicethat controls the enteral feeding into the patient.

Before explaining at least one embodiment of the invention in detail, itis to be understood that the invention is not necessarily limited in itsapplication to the details of construction and the arrangement of thecomponents and/or methods set forth in the following description and/orillustrated in the drawings and/or the Examples. The invention iscapable of other embodiments or of being practiced or carried out invarious ways.

The present invention may be a system, a method, and/or a computerprogram product. The computer program product may include a computerreadable storage medium (or media) having computer readable programinstructions thereon for causing a processor to carry out aspects of thepresent invention.

The computer readable storage medium can be a tangible device that canretain and store instructions for use by an instruction executiondevice. The computer readable storage medium may be, for example, but isnot limited to, an electronic storage device, a magnetic storage device,an optical storage device, an electromagnetic storage device, asemiconductor storage device, or any suitable combination of theforegoing. A non-exhaustive list of more specific examples of thecomputer readable storage medium includes the following: a portablecomputer diskette, a hard disk, a random access memory (RAM), aread-only memory (ROM), an erasable programmable read-only memory (EPROMor Flash memory), a static random access memory (SRAM), a portablecompact disc read-only memory (CD-ROM), a digital versatile disk (DVD),a memory stick, a floppy disk, and any suitable combination of theforegoing. A computer readable storage medium, as used herein, is not tobe construed as being transitory signals per se, such as radio waves orother freely propagating electromagnetic waves, electromagnetic wavespropagating through a waveguide or other transmission media (e.g., lightpulses passing through a fiber-optic cable), or electrical signalstransmitted through a wire.

Computer readable program instructions described herein can bedownloaded to respective computing/processing devices from a computerreadable storage medium or to an external computer or external storagedevice via a network, for example, the Internet, a local area network, awide area network and/or a wireless network. The network may comprisecopper transmission cables, optical transmission fibers, wirelesstransmission, routers, firewalls, switches, gateway computers and/oredge servers. A network adapter card or network interface in eachcomputing/processing device receives computer readable programinstructions from the network and forwards the computer readable programinstructions for storage in a computer readable storage medium withinthe respective computing/processing device.

Computer readable program instructions for carrying out operations ofthe present invention may be assembler instructions,instruction-set-architecture (ISA) instructions, machine instructions,machine dependent instructions, microcode, firmware instructions,state-setting data, or either source code or object code written in anycombination of one or more programming languages, including an objectoriented programming language such as Smalltalk, C++ or the like, andconventional procedural programming languages, such as the “C”programming language or similar programming languages. The computerreadable program instructions may execute entirely on the user'scomputer, partly on the user's computer, as a stand-alone softwarepackage, partly on the user's computer and partly on a remote computeror entirely on the remote computer or server. In the latter scenario,the remote computer may be connected to the user's computer through anytype of network, including a local area network (LAN) or a wide areanetwork (WAN), or the connection may be made to an external computer(for example, through the Internet using an Internet Service Provider).In some embodiments, electronic circuitry including, for example,programmable logic circuitry, field-programmable gate arrays (FPGA), orprogrammable logic arrays (PLA) may execute the computer readableprogram instructions by utilizing state information of the computerreadable program instructions to personalize the electronic circuitry,in order to perform aspects of the present invention.

Aspects of the present invention are described herein with reference toflowchart illustrations and/or block diagrams of methods, apparatus(systems), and computer program products according to embodiments of theinvention. It will be understood that each block of the flowchartillustrations and/or block diagrams, and combinations of blocks in theflowchart illustrations and/or block diagrams, can be implemented bycomputer readable program instructions.

These computer readable program instructions may be provided to aprocessor of a general purpose computer, special purpose computer, orother programmable data processing apparatus to produce a machine, suchthat the instructions, which execute via the processor of the computeror other programmable data processing apparatus, create means forimplementing the functions/acts specified in the flowchart and/or blockdiagram block or blocks. These computer readable program instructionsmay also be stored in a computer readable storage medium that can directa computer, a programmable data processing apparatus, and/or otherdevices to function in a particular manner, such that the computerreadable storage medium having instructions stored therein comprises anarticle of manufacture including instructions which implement aspects ofthe function/act specified in the flowchart and/or block diagram blockor blocks.

The computer readable program instructions may also be loaded onto acomputer, other programmable data processing apparatus, or other deviceto cause a series of operational steps to be performed on the computer,other programmable apparatus or other device to produce a computerimplemented process, such that the instructions which execute on thecomputer, other programmable apparatus, or other device implement thefunctions/acts specified in the flowchart and/or block diagram block orblocks.

The flowchart and block diagrams in the Figures illustrate thearchitecture, functionality, and operation of possible implementationsof systems, methods, and computer program products according to variousembodiments of the present invention. In this regard, each block in theflowchart or block diagrams may represent a module, segment, or portionof instructions, which comprises one or more executable instructions forimplementing the specified logical function(s). In some alternativeimplementations, the functions noted in the block may occur out of theorder noted in the figures. For example, two blocks shown in successionmay, in fact, be executed substantially concurrently, or the blocks maysometimes be executed in the reverse order, depending upon thefunctionality involved. It will also be noted that each block of theblock diagrams and/or flowchart illustration, and combinations of blocksin the block diagrams and/or flowchart illustration, can be implementedby special purpose hardware-based systems that perform the specifiedfunctions or acts or carry out combinations of special purpose hardwareand computer instructions.

As used herein, the term energy expenditure may sometimes beinterchanged with the term resting energy expenditure. The terms energyexpenditure and resting energy expenditure, as used herein, refer to theindigenous un-intervened energy also known as resting energy (e.g.,calorie) requirements of the monitored patient.

As used herein, the term enteral feeding may be sometimes interchangedwith the term tube feeding. The terms enteral feeding and tube feeding,as used herein, refer to feeding of the patient via a tube inserted intothe stomach of the patient. The tube is inserted into the stomach (orduodenum, or jejunum, or other locations in the digestive track) via thenose, the mouth, or a surgically created opening.

Reference is now made to FIG. 1A, which is a flowchart of a method ofdynamically adjusting an enteral feeding controller that controls theenteral feeding rate according to an estimate of energy expenditurecomputed based on output of sensors, in accordance with some embodimentsof the present invention. Reference is also made to FIG. 1B, which is aflowchart of a modified method of dynamically adjusting an enteralfeeding device for controlling the feed rate according to an estimate ofthe energy expenditure computed based on output of sensors andsupplementing the feed formula with extra protein, in accordance withsome embodiments of the present invention. The protein may besupplemented according to the level recommended by the care taker (i.e.,user), and/or automatically selected by code. A continuous feedingregimen or intermittent feeding regimen may be automatically selected bycode, and/or manually selected by the care taker (i.e., user).

If vital signs indicate that the patient is not in resting status theadditional implementation of the method is to be halted until thepatient is determined to be in the resting state. Monitoring of thepatient may continue to determine when the patient enters the restingstate.

Reference is also made to FIG. 2, which is a schematic of components ofa system 200 for estimating energy expenditure based on output of one ormore sensors 202A-C, and generating instructions for adjustment of theenteral feeding rate provided by an enteral feeding controller 204according to the estimated energy expenditure, in accordance with someembodiments of the present invention. One or more acts of the methoddescribed with reference to FIGS. 1A and/or 1B may be implemented bycomponents of system 200, as described herein, for example, by aprocessor(s) 206 of a computing device 208 executing code instructionsstored in a memory (also referred to as a program store) 210 (othervital signals for example blood saturation and other analytes may beincorporated into the calculations).

Computing device 208 receives electrical signals outputted by one ormore oxygen sensors 202A, and/or one or more carbon dioxide sensors202B. Computing device 208 may receive electrical signals outputted byone or more nitrogen sensors 202C. Oxygen sensor(s) 202A and/or carbondioxide sensor(s) 202B measure inspiration and/or expiration of thepatient (e.g., that occur naturally by respiration of the patient and/oroccur by an external device forcefully ventilating the patient). Sensors202A-B may be, for example, located within a ventilation device thatprovides oxygen to the patient, for example, within a ventilation tube(e.g., endotracheal tube) in a mechanically ventilated patient, within aVenturi mask and/or nasal cannula on a patient breathing on their own,and/or within components of the mechanical ventilation machine and/orcomponents associated with the Venturi mask. Nitrogen sensor(s) 202C maybe located, for example, within a urinary catheter, within a urinecollection bag, and/or within other urine flow devices and/or urinecollection devices (and optionally other vital signals for example bloodsaturation may be incorporated into the calculations).

Computing device 208 may receive the outputs of one or more sensors202A-C via one or more sensor interfaces 212, for example, a networkinterface, a wire connection, a wireless connection, a local bus, otherphysical interface implementations, and/or virtual interfaces (e.g.,software interface, application programming interface (API), softwaredevelopment kit (SDK)).

Computing device 208 may be implemented as, for example, a standaloneunit, a client terminal, a server, a computing cloud, a mobile device, adesktop computer, a thin client, a Smartphone, a Tablet computer, alaptop computer, a wearable computer, glasses computer, and a watchcomputer. Computing device 208 may be implemented as a customized unitthat include locally stored software and/or hardware that perform one ormore of the acts described with reference to FIGS. 1A and/or 1B.Alternatively or additionally, computing device 208 may be implementedas code instructions loaded on an existing computing device.Alternatively or additionally, computing device 208 may be implementedas hardware and/or code instructions (e.g., an accelerator card)installed and/or integrated within an existing computing device.

Processor(s) 206 of computing device 208 may be implemented, forexample, as a central processing unit(s) (CPU), a graphics processingunit(s) (GPU), field programmable gate array(s) (FPGA), digital signalprocessor(s) (DSP), and application specific integrated circuit(s)(ASIC). Processor(s) 206 may include one or more processors (homogenousor heterogeneous), which may be arranged for parallel processing, asclusters and/or as one or more multi core processing units.

Memory (also known herein as a data storage device) 210 stores codeinstructions executable by processor(s) 206, for example, a randomaccess memory (RAM), read-only memory (ROM), and/or a storage device,for example, non-volatile memory, magnetic media, semiconductor memorydevices, hard drive, removable storage, and optical media (e.g., DVD,CD-ROM). Memory 210 stores code instruction that implement one or moreacts of the method described with reference to FIGS. 1A and/or 1B.Alternatively or additionally, one or more acts of the method describedwith reference to FIGS. 1A and/or 1B are implemented in hardware.

Computing device 208 may include a data storage device 214 for storingdata, for example, feeding database 214A that stores records ofcomposition of enteral feeding formulations, for example, from differentvendors. Data storage device 214 may be implemented as, for example, amemory, a local hard-drive, a removable storage unit, an optical disk, astorage device, and/or as a remote server and/or computing cloud (e.g.,accessed via a network connection).

Computing device 208 includes and/or is in communication with a userinterface 216 that includes a mechanism for a user to enter data (e.g.,patient information, initial enteral feeding rate and/or composition)and/or view presented data (e.g., computed energy expenditure, changesto the enteral feeding rate and/or changes to the composition of theenteral feeding). Exemplary user interfaces 216 include, for example,one or more of, a touchscreen, a display, a keyboard, a mouse, and voiceactivated software using speakers and microphone. External devicescommunicating with computing device 208 may serve as user interfaces216, for example, a smartphone running an application may establishcommunication (e.g., cellular, network, short range wireless) withcomputing device 208 using a communication interface (e.g., networkinterface, cellular interface, short range wireless network interface).The user may enter data and/or view data on the display of thesmartphone, optionally via a graphical user interface (GUI) application.

Computing device 208 includes a device interface 218 that provideselectrical communication with an enteral feeding controller 204 thatcontrols enteral feeding of the patient via an enteral feeding tube.Enteral feeding controller 204 controls and/or adjusts the rate of theenteral feeding according to instructions generated by computing device208 in response to the estimated energy expenditure computed based onoutput of sensor(s) 202A-B and optionally sensor 202C. Enteral feedingcontroller 204 (and/or another device) may adjust the composition of theenteral feeding according to instructions generated by computing device208. Device interface 218 may be implemented as, for example, a networkinterface card, a hardware interface card, a wireless interface, aphysical interface for connecting to a cable, a virtual interfaceimplemented in software, communication software providing higher layersof connectivity, and/or other implementations. Enteral feedingcontroller 204 may be implemented using a mechanical based mechanism,and/using computer components (e.g., processor(s), memory storing codeinstructions executable by the processor(s), and/or hardwarecomponents). Enteral feeding controller 204 may be implemented as a pump(e.g., positive displacement feed pump) that is controlled to deliverenteral feedings to the patient via the enteral feeding tube accordingto the rate defined by the instructions generated by computing device208. Enteral feeding controller 204 may include a valve that selectivelyopens the lumen of the enteral feeding tube so that enteral feeding maybe delivered to the patient at the defined rate.

Enteral feeding controller 204 may include a feeding selecting mechanismthat controls delivery of multiple formulations, each at a defined rate.For example, a valve that selects between two tubes, each providing adifferent formulation at a respective different feeding rate, accordingto the generated instructions. It is noted that an increase of theprotein percentage in the feeding formula may be manually selected bythe user and/or automatically selected by code as shown schematicallywith reference to FIG. 1B.

Referring now back to FIG. 1A, at 102, an initial enteral feeding rateand/or initial enteral feeding composition is set. The initial enteralfeeding rate and/or initial enteral feeding composition may be enteredinto computing device 208, for example, manually by the user via userinterface 216, for example, via a graphical user interface (GUI)presented on a display, automatically computed based on one or morevalues manually entered and/or automatically obtained from storage(e.g., from an electronic health record). For example, the basalmetabolic rate, which may be used to set the initial estimated energyexpenditure and/or corresponding initial feeding rate and/or initialfeeding composition, may be computed according to the Harris-Benedictequation. The initial enteral feeding rate and/or initial enteralfeeding composition may be based on a manual subjective observation ofthe current status of the patient and/or according to available feedingmaterials (e.g., stock). The initial enteral feeding composition may beselected, for example, based on body parameters (e.g., weight, height,age) according to current practice (e.g., ICU best practices).

The initial enteral feeding rate and/or initial enteral feedingcomposition is dynamically adjusted, as described herein with referenceto acts 104-116. The adjustment may be performed continuously, triggeredbased on detected events, and/or at predefined time intervals. Theadjustment is performed in real time, without a significant and/ordetectable delay.

Optionally, a mismatch between the computed estimate of energyexpenditure (as described with reference to act 106) and the initialstate is computed. The instructions for adjusting the initial state ofthe enteral feeding controller 204 are generated according to thecomputed mismatch (as described with reference to act 112).

Optionally, at 103, an analysis is performed to determine whether thepatient is at rest. Optionally, the resting energy expenditure iscomputed (as described herein) when the patient is determined to be atrest. When the patient is not at rest, the initial programmed and/ormanually determined patient feeding setting may be continued, asdescribed with reference to act 102.

The determination of whether the patient is resting or not may bedetermined, for example, by a set-of-rules applied to patient data. Forexample, an analysis of data obtained from patient monitoring sensors(and/or devices) and/or obtained from an electronic health record may bemade to determine whether the patient is at rest. The electronic medicaland/or health record of the patient may be accessed by computing device208 via a network interface, for example via HL7 protocol. Computingdevice 208 may receive patient data, optionally patient vital signmeasurements, optionally in real-time and/or near real-time (e.g.,within about 1 minute, 5 minutes, 10 minutes, or other values).Exemplary patient data that is analyzed to determine rest (or not)includes one or more of: heart rate, blood pressure, oxygen saturation(e.g., measured manually by nurses, and/or automatically by a devicesuch as a pulse oximetry and/or sphygmomanometer). For example, apatient with a baseline normal heart rate experiencing tachycardia (fastheart rate), for example, due to stimulation (e.g., medical procedurebeing performed, stress), may not be considered at rest.

When the patient is not at rest, the patient data may be monitored(e.g., continuously and/or at short intervals, for example, every 5, 10,15 minutes or other values) to determine whether the patient entered therest state. Alternatively, when the patient is determined to be resting,the patient data may be monitored to determine whether the patient isstill resting or entered a non-rest state.

When the patient is determined to not be at rest, an alert may begenerated indicative of the lack of rest state of the patient, forexample, as a message displayed on the GUI.

At 104, an oxygen measurement outputted by an oxygen sensor(s) 202A anda carbon dioxide measurement outputted by a carbon dioxide sensor(s)202B associated with a ventilation device (e.g., ventilation tube, mask)of the patient is received by computing device 208, optionally viasensor interface 212.

Oxygen and/or carbon dioxide measurements are performed on inspired airand/or expired air.

The net oxygen flow rate (i.e., into the patient) and the net carbondioxide flow rate (i.e., out of the patient) may be computed. The netoxygen and carbon dioxide flow rates are indicative of indirectcalorimetry, based on the oxidation balance of carbohydrates (e.g.,glucose), fat, and/or protein, by the body of the patient.

Some embodiment(s) relate to performing the feed rate and compositioncalculations based on exhaled CO₂ sensing exclusively.

Optionally, a urine nitrogen measurement outputted by a nitrogensensor(s) 202C is received by computing device 208. The indirectcalorimeter computation (i.e., the estimate of energy expenditure) isdynamically computed according to the nitrogen measurement, as describedherein. The urine nitrogen measurement is indicative of proteinoxidation. The urine nitrogen measurement increased the precision of thecomputed estimated energy expenditure as an indirect calorimetryindication. Alternatively, the urine nitrogen may be computed as anapproximation, without measuring the nitrogen in the urine by thenitrogen sensor.

In terms of mathematical representation:

{dot over (V)} O₂ denotes the net flow of oxygen (e.g., liters per min(L/min))

{dot over (V)} CO₂ denotes the net flow of carbon dioxide (e.g., litersper min (L/min))

{dot over (N)} denotes the net amount of nitrogen (e.g., gram per min(L/min))

$\overset{\_}{m} = \begin{bmatrix}{\overset{.}{V}{CO}\; 2} \\{\overset{.}{V}O\; 2}\end{bmatrix}$Denotes a measurement vector, CO2, O2 in [L/min]

$\overset{\_}{m} = \begin{bmatrix}{\overset{.}{V}{CO}\; 2} \\{\overset{.}{V}O\; 2} \\\overset{.}{N}\end{bmatrix}$Denotes the measurement vector, CO2, O2 in [L/min] and nitrogen[gram/min]

Optionally, at 105, one or more clinical parameters of the patient areset. The clinical parameters may be manually entered by a user (e.g.,via the GUI), automatically computed (e.g., based on sensor data and/orother data obtained for example from the electronic health record of thepatient) and/or retrieved from a data storage device (e.g. from theelectronic health record of the patient).

The clinical state of the patient may be received. The clinical state ofthe patient may include one or more medical diagnoses of the patient.The clinical state of the patient may affect computation of the targetfeeding composition. Exemplary clinical states include: maintenance,stressed/MICU, trauma/general surgery, trauma/ICU, burn(s), cancer,obesity (e.g., body mass index (BMI) >29.9).

The weight of the patient may be received. The weight of the patient mayaffect computation of the target feeding composition.

Patients with different clinical states and/or different weights mayhave different nutritional goals, which may affect computation of thetarget composition and/or target feeding rate.

At 106, an estimate of energy expenditure of the patient is dynamicallycomputed based on the oxygen measurement, the carbon dioxidemeasurement, and optionally the nitrogen measurement. The estimate ofenergy expenditure is dynamically computed as a rate of energyexpenditure for a predefined time duration during which the oxygen andcarbon dioxide measurements are obtained, for example, over about aminute, 5 minutes, 15 minutes, 30 minutes, 1 hour, or other timeintervals. Alternatively, when intermittent feeding is selected (asdescribed herein), the estimate of energy expenditure may be dynamicallycomputed during the intermittent feeding intervals. Energy expendituremay not necessarily be computed during between the intermittent feedingintervals when no feeding is occurring.

It should be noted that the calculations are leading to neededcomposition of the feeding material and are not necessarily limited toflow rate only.

Energy expenditure denotes an accurate indicator for intake of foodrequirements of patients, in particular patients in an ICU (or similar)setting. The estimate of energy expenditure represents an estimate ofcaloric expenditure of the patient. The estimate of energy expenditureis computed based on metabolic rate estimated from oxygen consumptioncomputed based on the oxygen measurement, and carbon dioxide productioncomputed based on the carbon dioxide measurement. As discussed herein,the enteral feeding controller dynamically adjusts the enteral feedingrate to deliver calories to the patient, to replenish the caloricexpenditure according to the computed estimate.

Since as discussed herein, the energy expenditure of the enteral fedpatient may be assumed to be resting energy expenditure, the estimate ofthe energy expenditure (i.e., resting energy expenditure (REE)) may becomputed according to the Weir equation (or other corresponding and/orsimilar methods), mathematically represented as follows:

${{REE}\left\lbrack \frac{kJ}{day} \right\rbrack} = {\left\lbrack {16.2,5,{- 6}} \right\rbrack \cdot \overset{\_}{m}}$

${{REE}\left\lbrack \frac{kJ}{day} \right\rbrack} = {{{16.2 \cdot \overset{.}{V}}O\; 2} + {{5 \cdot \overset{.}{V}}{CO}\; 2} - {6\overset{.}{\cdot N}}}$

When oxygen measurements are not available (e.g., no oxygen sensor isinstalled, the oxygen sensor fails), the REE may be calculated based onthe carbon dioxide measurement and an assumed and/or estimated value forrespiratory quotient (RQ), for example, 0.85. Alternatively, when oxygenmeasurements are available, RQ may be calculated, and food compositionmay be adjusted accordingly.

Optionally, a prediction of future energy expenditures is computed basedon current and/or historical sensor measurements. The prediction may bebased on, for example, detection of similar previously observedpatterns. For example, the patient may experience different energyexpenditures at different times of the day, such as during the day andduring the night. The prediction may be performed based on detectedpatterns, for example, detection of an onset of the nighttime patternindicative of relatively lower energy expenditure for an upcoming periodof time. The prediction may be computed, for example, by machinelearning code instructions (e.g., neural network) that is trained onhistorical sensor measurements (and optionally corresponding computedenergy expenditures) and performs prediction.

At 108, a target composition and/or rate of the enteral feeding iscomputed. The target composition and/or target rate denotes the bestmatching food rate and/or composition for the patient. Optionally, anadjustment of the existing enteral feeding composition and/or initialset rate to arrive at the target composition and/or target rate iscomputed. As the patient's condition changes (e.g., due to stress,recovery, movement, medication administration, infection), the idealcomposition requirements for the patient change, and are met by thedynamic computation of the target feeding composition and/or target ratefor which a similar available feeding formulate is selected.

Optionally, the target composition and/or feeding rate is evaluatedrelative to the current enteral feeding composition and/or feeding rateaccording to a requirement, for example, an absolute difference and/orrelative difference (e.g., over 5%, or 10%, or 20%, or over 10 cc/hour,or 25 cc/hour, or over 100 calories, or over 150 calories, or othervalues). When the requirement is not met, no change to the targetcomposition and/or feeding rate is necessarily required. The energyexpenditure may be re-computed at a future point in time to determinewhen the requirement is met.

Optionally, the target composition and/or target feeding rate includesan amount of water, which may be added separately to an available powdercomposition and/or powder protein composition. The ratio between theamounts of water to be added to a certain amount of powder may becomputed, optionally according to the ratio of water to powder currentlybeing delivered and/or recently provided.

The target composition and/or rate of the enteral feeding may becomputed in view of the patient clinical condition and/or patient weight(e.g., as described with reference to act 105).

The target composition and/or rate of the enteral feeding may becomputed according to the nutritional goal of the patient.

The target rate of delivery of the enteral feeding is computed accordingto the estimate of energy expenditure in view of the target feedingcomposition.

The enteral feeding delivery rate that is controlled by the enteralfeeding device may be mathematically represented as, where cc denotescubic centimeters, and hr denotes per hour:{dot over (f)}[cc/hr]

The target composition of the enteral feeding is computed according tothe computed estimate of energy expenditure. The target composition mayinclude defined amounts (e.g., weight, percentage) of glucose (denotedġ), lipids (denoted {dot over (l)}), and/or protein (denoted {dot over(p)}). The target composition may be represented as a feeding vector,which may be mathematically represented as:

$\overset{.}{f} = \begin{bmatrix}\overset{.}{g} \\\overset{.}{l} \\\overset{.}{p}\end{bmatrix}$

The feeding vector (i.e., composition, for example, glucose, lipids,and/or protein), may be computed based on the computed estimate ofenergy expenditure, and/or indirect calorimetry vector m, for example,as described by Eric Jequier, Kevin Acheson, and Yves Shutz, “Assessmentof Energy Expenditure and Fuel Utilization in Man”, Ann. Rev. Nutr.1987. 7:187-208.

It should be made clear that the equations presented herein areexemplary and not necessarily limiting. It is noted that future researchmay recommend modification of the described equations and/or suggest newequations. The systems, apparatus, methods, and/or code instructionsdescribed herein implement such new and/or modified equations by thecontroller.

The target composition may be computed in accordance for reaching anutritional goal of the patient. The nutritional goal may be determined,for example, based on an aggregation of data collected from multiplesampled individuals, based on clinical evidence, based on expert opinionstored in a database, optionally based on machine learning methods thatthe analyze patient data and/or the clinical evidence and/or the expertopinion. Optionally, the target composition is computed based on anaggregation of data collected from multiple sampled individuals. Thetarget composition may be computed according to a probability ofobtaining the best outcome (e.g., recovery, improved survival). Forexample, different compositions fed to different patients, and theexperienced outcomes (e.g., recovery, improved survival, death,discharge, re-admittance). The target composition may be computed, forexample, by machine learning code instructions (e.g., neural network)that is trained on data of multiple other patients (e.g., providedcomposition, outcome) and computes the composition most likely to leadto the best outcome (e.g., recover, improved survival). Optionally,feeding database 214A is searched to identify one or more records ofavailable feeding formulations according to the computed targetcomposition (e.g., the feeding vector). Optionally, when no exactmatching record is available, the closest matching records are found.The closest matching records may be ranked according a similarityrequirement to the target composition. The closest matching records maybe computed, for example, based on a least square fit, based on a bestfit parameter, a correlation parameter, a computed statistical distance,or other measurements of similarity requirement that indicate similaritybetween datasets (e.g., vector distance).

Optionally, when no available matching records are found (i.e.,according to the similarity requirement), components of the computedtarget composition may be matched independently and/or in sets torecords of feeding database 214A. For example, for a certain patient, apure protein component of the target composition may be computed, forexample, as described in additional detail with reference to FIG. 1B.When no available matching record is found that includes pure protein,the other components may be matched to a certain formulation record, andthe pure protein may be matched to another record (for example, providedas an adviser to the treating physician and will depend on his/herdecision).

Feeding database 214A may be locally stored on computing device 208,and/or remotely stored (e.g., on a data storage device, network server,computing cloud) and accessed for example over a network.

Reference is now made to FIG. 3, which is a schematic depicting anexample of a record of a certain enteral feeding product formulation, inaccordance with some embodiments of the present invention. Data for theformation depicted in FIG. 3 is stored as a record in feeding database214A. The formulation depicted in FIG. 3 may be selected and/or rankedfor a similar computed target composition, according to the similarityrequirement.

The identified matching records of feeding formulations may be presentedon a display, for example, within a GUI. Optionally, a ranking scoreindicative of the similarity between the matching record and the targetcomposition is presented. The identified matching records may or may notbe physically available in stock. The presentation of multiple recordsthat are the most similar to the target composition enables the user tochoose the formulation that is actually available in stock.

Optionally, a change in composition of the feeding formulation isautomatically suggested. The change may be suggested when the newlycomputed target composition is significantly different from the currentfeeding formulation being provided (e.g., which may have been previouslyselected by the user), for example, according to a similarityrequirement. One or more suggested newly computed target compositionsmay be presented to the user on the display, for example, within theGUI.

Referring now back to FIG. 1, at 110, the user may manually select thefeeding composition(s) to feed the patient from the list of matchingrecords that represent the closest compositions to the computed targetcomposition. For example, the user may manually click within the GUIpresented on the display to select the feeding composition.

Optionally, a mismatch is identified between a currently computedavailable feeding composition and a previously computed availablefeeding composition. The mismatch may be corrected by computing theadditional feeding composition (e.g., as described with reference toFIG. 1B) for providing the currently computed available feedingcomposition.

The selected composition may be obtained and connected to enteralfeeding controller 204. The feeding tube may be primed and prepared todeliver the selected composition to the patient.

Alternatively, the selection of the composition may be automaticallyperformed by computing device 208. The selected composition may beautomatically connected to enteral feeding controller 204. The user maybe asked to verify the automated selection, for example, by clicking OKon a display. The automatic connection of the selected feedingcomposition may be performed, for example, by a robotic system thatautomatically retrieves the selected composition and connects theselected composition, or for example, multiple compositions may bepre-set with the final connection to the enteral feeding controllerperformed automatically by a connection mechanism.

Optionally, additional additives are added to the selected feedingmaterials. The additional additives may be manually added by the user,and/or automatically inserted by an automated system (e.g., robot). Theadditional additives include materials not defined by the targetcomposition. For example, when the target composition includes glucose,fat, and protein, the additional additives may include nutrients (e.g.,vitamins, minerals), fiber, and/or other substances.

Alternatively or additionally, when no nitrogen measurement is available(and/or when a user manually selects to ignore the nitrogenmeasurements), an enhanced protein diet may be added to the targetcomposition. The enhanced protein diet may be selected based on researchevidence showing benefit in reducing mortality. For example, about1.2-2.0 gram (gm) of protein per kilogram (Kg) of body weight, forexample, about 1.5 gr/Kg. The protein may be considered as an additive,since nitrogen measurement values are not considered in computing thetarget composition. The target composition may be computed based oncaloric demand.

At 112, instructions for adjustment of the feeding rate by enteralfeeding controller 204 are automatically generated by computing device208. The adjustment may be provided, for example, as a new feeding rate,or a change from the existing feeding rate.

It is noted that computing device 208 may be integrated with enteralfeeding controller, or computing device 208 may exist as an independentdevice that transmits the generated instructions to enteral feedingcontroller 204.

The rate of delivery of the enteral feeding, when different from thecomputed target feeding rate, may be adjusted accordingly. For example,when the selected feeding composition is different than the targetfeeding com position, the actual rate of delivery may be adjustedaccordingly.

Optionally, another set of instructions is generated. The second set ofinstructions may be integrated with the first set of instructions (e.g.,provided to a common controller), and/or the first and secondinstructions may be outputted to two independent controllers (which maysynchronize with one another). The second set of instructions may defineadjustment of the rate of the second component(s) of the selectedenteral feeding formulation, for example, the pure protein componentdiscussed herein with reference to act 108 and/or as described withreference to FIG. 1B. It is noted that three or more sets ofinstructions may be generated according to the number of independentlymatched sets of components. Each instruction set defines the rate ofdelivery of the respective components of the enteral formulation, forexample, independent rates for each of glucose, fat, protein, and/orother nutrients.

Optionally, the instructions for dynamic adjustment of the enteralfeeding by the enteral feeding controller are set below a refluxgenerating feeding level (e.g., threshold, range) estimated to triggerreflux of the enteral feeding by the patient. Controlling to feedingrate to remain below the reflux feeding level may prevent or reducereflux of the enteral feedings by the patient, which may reduce orprevent related complications such as aspiration pneumonia. The refluxfeeding level may be computed according to the net food portion of anestimated gastro residual volume (GRV). The estimate of the GRV may becomputed, for example, based on weight, volume, and specific gravity ofthe enteral feeding delivered by the enteral feeding pump. One method ofmaking decisions regarding enteral feeding involves manually measuringthe volume of digestive contents in the patient's stomach after anenteral feeding session, by using a syringe to aspirate the stomachcontents. The measured volume is termed Gastric Residual Volume (GRV).The value of the GRV is used by healthcare professional to decide, forexample, if the patient received enough food, is having problemsingesting the delivered food, and/or if the patient is at increased riskof aspiration pneumonia. For example, when the measured GRV is above athreshold, the next enteral feeding is delayed. A full assessment usingGRV may take up to 72 hours, with 4 hour intervals between GRVmeasurements. Computing the estimate of the GRV as described herein mayreduce or prevent procedures for direct measurement of the GRV, forexample, according to common practice: withdrawing the contents of thestomach, measuring the volume of the withdrawn contents, and returningthe withdrawn contents back into the stomach.

The GRV measured may be used for modification of the feed rate accordingto:

${V_{f}({modified})} = {V_{f} - \frac{W_{GRV}}{{\rho_{GRV} \cdot \Delta}\; t}}$

Where WGRV denotes the weight of the collected GRV, Vf denotes thevolume of the enteral formulation, ρ_(GRV) denotes the specific gravityof the collected GRV, and Δt denotes the accumulation period, forexample 1 hour.

The energy consumption based computed rate of the enteral feeding may bemanually and/or automatically reduced accordingly in view of thecomputed GRV and threshold. The target composition may be adjustedaccordingly, for example, to compensate for the adjusted in the rate.For example, the reduction in rate to avoid reflux may reduce theprotein the patient requires. The target composition may be adjusted toinclude additional protein to make up for the potential loss of proteinat the reduced rate.

Optionally, the feeding rate is personalized based on historical feedingperformance. The personalization may be performed, for example, based onhistorical data indicating that the patient is able to handle a feedingrate without reflux, which is 75% below the reflux threshold otherwisecomputed. The personalization may be based on, for example, an analysisof positive and/or negative feeding performance. For example, thepatient may reflux at different reflux thresholds at different times ofthe day, such as during the day and during the night. Thepersonalization may be computed, for example, by machine learning codeinstructions (e.g., neural network) that is trained on historicalfeeding performance (e.g., feeding rates, indications of reflux or noreflux) and performs the personalization.

At 114, enteral feeding controller 204 implements the receivedinstructions, and controls delivery of the selected enteral compositionaccording to the computed rate.

Optionally, in the case of receiving the two sets of instructions (e.g.,the separate sets, and/or the combined sets), the two sets ofinstructions are implemented by enteral feeding controller 204. Forexample, the two sets of instructions may be implemented by alternatingdelivery of the two compositions, each at a respective rate (i.e.,sequential delivery). In another example, the two sets of instructionsmay be implemented in parallel, for example, delivering two compositionseach at a respective rate.

Optionally, the first and second set of generated instructions control afeed selecting mechanism (e.g., pinch valve) that selects between afirst tube that delivers the enteral feeding (or other selected set ofcomponent(s)) and a second tube that delivers the protein component (orother set of component(s)). The first tube and the second tube mayconnect into a combined tube that provides the enteral feeding of thepatient, or each tube may independently provide the enteral feeding(i.e., without the combined tube).

Reference is now made to FIG. 4, which is a schematic of an exemplaryimplementation of the enteral feeding device (e.g., 204 of FIG. 2) forindependent control of the rate of delivery of two components of theenteral feeding, in accordance with some embodiments of the presentinvention. Enteral feeding device 204 includes one standard feed inlet402 of a first tube F through which the standard selected enteralfeeding composition is provided (i.e., a first set of components), andanother feed inlet 404 of a second tube P through which the selectedprotein supplement (i.e. a second set of components) is provided, inaccordance with some embodiments of the present invention. A feedselecting pinch valve 406 (or other implementation of a selectionswitch) controls which of the two tubes F and P supplies its respectivecontents to pump head 408 for delivery to the patient via tube outlet410. Feed selecting pinch valve 406 alternatively switches betweenprotein tube P and standard feeding tube F to obtain the selectedcomposition, which is delivered to the patient by pump 408.

At 116, data is presented on a display (e.g., user interface 216),optionally within a graphical user interface (GUI). The presented datamay be dynamically updated accordingly.

Exemplary data presented on the display include one or more of:

-   -   Current computed estimated energy expenditure, for example, as a        numerical value.    -   A trend based on history of the computed energy expenditure, for        example, presented as a graph denoting a trend line plotting        based on previously computed points indicative of estimated        energy expenditures.    -   Current feeding rate delivered by the enteral feeding pump.    -   Computed target composition, selected formulation, and        similarity between the target composition and the selected        formulation.

The presented data may be saved in a log, database, and/or other datastructure, for example, stored in data storage device 214 and/or anotherstorage device. The stored data may be analyzed off-line, for example, ameta-analysis of feeding effectiveness may be computed based on datacollected from multiple patients.

At 118, one or more features described with reference to acts 104-116are iterated. The iterations are performed to dynamically adjust theenteral feeding rate according to dynamics of the current energyexpenditure of the patient.

The iterations may be performed, for example, continuously (e.g., whensensor measurements are analogue signals) or near continuously (e.g.,when digital sampling is performed), at predefined time intervals (e.g.,one minute between iterations, or other values, for example, less thanabout 5, 10, 15, 30, 60 minutes, or other time intervals betweeniterations), and/or at triggers (e.g., detection of an increase in heartrate, manual selection by a user, administration of medication).

Optionally, the sensor measurements and the computation of the energyexpenditure are performed iteratively according to a first rate and/orfirst time interval, for example, to perform continuous and/or nearcontinuous real time monitoring, for example, less than about 5, 10, 15,30, 60 minutes, or other time intervals. The instructions for adjustmentof the enteral feeding may be iterated at a second time interval that islarger than the first time interval, for example, at least every 30minutes, 60 minutes, 120 minutes or other values. In this manner, thepatient may be continuously monitored for changes in energy expenditure,while the actual formula and/or rate changes occur less frequently.

Optionally, the feeding rate provided by the enteral feeding pump isdynamically adjusted to match the rate of energy expenditure within atolerance requirement. The enteral feeding pump may perform localmonitoring and/or control over the actual delivered feeding rate, tomaintain the instructed feeding rate within the tolerance requirement.For example, a closed loop may include local sensors to measure theactual delivered feeding rate and a valve to adjust the actual feedingrate accordingly.

The iterations correct the difference (e.g., error) between the initialsettings of the feeding rate and/or composition (e.g., as described withreference to act 102) and the actual patient requirements estimated bythe computed energy expenditure and/or corresponding computedcomposition. Equilibrium may be reached between the estimated energyexpenditure and the provided enteral feeding (i.e., rate and/orcomposition) as the difference is reduced.

Referring now back to FIG. 1B, acts 102-110 are as described withreference to FIG. 1A.

At 119, an analysis is performed (e.g., by code instructions stored inmemory 210 executed by hardware processor(s) 206 of computing device208) to determine whether the calories and protein of the selectedcomposition (which may match the target composition, or may representthe closest available match to the target composition, as describedherein) match within a tolerance to the computed REE of the patient.

At 120, supplemental protein is added to the selected feedingformulation when the protein content of the selected feeding formulationis determined to be insufficient for meeting patient needs computedbased on the REE.

When protein provided by the selected feeding formulation is determinedto be insufficient, the amount of supplemental protein to meet patientrequirements is computed.

It is noted that the supplemental protein may be added withoutsignificantly increasing the caloric and/or volumetric feeding ratecomputed for the selected composition. The selected composition may notnecessarily require re-computation and/or re-selection in view of thecomputed supplemental protein. For example, supplemental protein may beadded as a powder mixed into the liquid selected feeding composition.Alternatively, the feeding rate of the supplemental protein isindependently computed and delivered, as described herein.

The amount of supplemental protein may be presented on the GUI and/orstored in memory for further processing. Commercially available proteinsupplements (e.g., that are currently available in stock) may bepresented on the GUI, and/or stored in memory for further processing.

Supplemental protein may be added as follows:

-   -   Manually by a user. The GUI may present the computed REE and/or        supplemental protein requirements. The user may view the list of        available protein supplements, and make a manual selection. The        user may mix the protein supplement within the selected feeding        composition, and/or connect the selected protein supplement to        the dual feeding pump, as described herein (e.g., with reference        to FIG. 4).    -   Semi-automatically by the user and code. Based on the computed        REE, the target feeding composition, and available feeding        formulations, code instructions may compute the closest matching        available feeding formulation as described herein. The amount of        supplemental protein is computed according to available protein        supplements (e.g., stored in a database). The code instructions        may compute options of the closest matching protein supplements        according to availability (e.g., stored in a database). The GUI        may present the available options for user selection. The user        selects the protein supplement and connects the selected feeding        composition and protein supplement.    -   Fully automatic. Based on the computed REE, the target        composition, and available formulations, code instructions may        compute the closest matching available formulation as described        herein. The code instructions may compute the amount and/or type        of supplemental protein that when added to the selected        composition arrives at the protein required by the patient        (i.e., to obtain 100% of the patient requirements). The amount        and/or type of supplemental protein is computed according to        available protein supplements (e.g., stored in a database). The        GUI may present instructions to the user to attach the selected        formulation and selected protein supplement to the pump, or to        mix the protein supplement and selected formulation (e.g., add        protein powder into the liquid formulation).

At 130, the feeding mode is selected. Feeding may be may be continuous,for example, a constant rate throughout the day (e.g., over 24 hours).Alternatively, feeding may be intermittent, for example, 1 hour feedingintervals followed by 5 hours of no feeding, repeated 4 times a day.Such intermittent feeding may let the gastric system of the patient restbetween consecutive feedings (e.g., more similar to normal eating ofmeals separated by no-eating intervals). The continuous and/orintermittent feeding may be variable and/or incremental (e.g., based ona function and/or set-of-rules), for example, initially set at 50% ofpatient feeding requirements, and rising to 100% of the patient feedingrequirements over a predefined time period (e.g., 3 days). Theincremental rise may be linear, exponential, or using otherimplementations.

The continuous or intermittent and optionally incremented feeding may beselected, for example, with reference to feeding loop 302 described withreference to FIG. 5, and/or act 114 and/or 118 described with referenceto FIG. 1A.

At 140, the feeding controller is set and the selected feedingcomposition and supplemental protein is delivered.

At 150, the actual feeding is monitored and/or data is presented on thedisplay, as described with reference to act 116 of FIG. 1A.

At 160, one or more features described with reference to acts 104-150are iterated. The iterations are performed to dynamically adjust theenteral feeding rate and/or the selected formulation and/or thesupplemental protein according to dynamics of the current resting energyexpenditure of the patient.

Reference is now made to FIG. 5, which is a dataflow diagram of dynamicadjustment of an enteral feeding rate by an enteral feeding controlleraccording to an estimated energy expenditure computed based on output ofsensor(s), in accordance with some embodiments of the present invention.The dataflow diagram described with reference to FIG. 5 depicts dataflowbased on the method described with reference to FIGS. 1A-B, and/orwithin an implementation based on components of system 200 describedwith reference to FIG. 2. The dataflow diagram described with referenceto FIG. 5 depicts a closed feedback loop 302, which adjusts the enteralfeeding rate and/or compositions according to changes in patientcondition detected based on sensor measurements.

Patient 10 denotes a mechanically ventilated and enteral fed patient(e.g., in the ICU). Indirect calorimetry 11 is performed to estimate theenergy expenditure of patient 10, to determine the enteral feeding formeeting the calorie expenditure of patient 10. Patient 10 is ventilatedvia a ventilator attachment 11C. Oxygen and carbon dioxide sensorsmeasure oxygen consumption and carbon dioxide production during patient10 inspiration 11 a and expiration 11 b via ventilator attachment 11 c.

Optionally, at 12, nitrogen output is measured by a urine sensor and/orestimated, for example, according to an estimated value of 1.3-2milligrams of protein produced per kilogram of body weight.

Optionally, at 103, the patient rest state is computed as described withreference to act 103 of FIG. 1A. When the patient is at rest, thefeedback loop 302 continues. When the patient is not at rest, thefeedback loop 302 is halted until the patient is determined to be atrest.

Optionally, at 105, clinical parameter(s) of the patient are set asdescribed with reference to act 105 of FIG. 1A.

At 15, the enteral feeding rate is calculated according to the estimatedenergy expenditure (optionally the resting energy expenditure) 11, whichis computed based on the measured oxygen consumption, carbon dioxideproduction, and nitrogen production. At 16, the composition of theenteral feeding may be selected according to a database of availablefeeding materials. Multiple enteral feeding products may be presentedfor use selection, optionally according to a ranking. The ranking maydenote a measure of similarity to the computed idea enteral feedingcomposition. The enteral feeding rate and/or composition of the enteralfeeding may be computed according to the clinical parameter(s) of thepatient.

Optionally, at 17, a display may present real time monitoring data,which may be stored in a logbook. The real time monitoring data may bepresented as a graph depicting trends over time in the computedestimated energy expenditure and/or the computed enteral feeding rate.The real time monitoring data may include the current and/orinstantaneous numerical value of the computed energy expenditure and/orfeeding rate, for example, in cubic centimeters (cc) per hour.

Optionally, at 15 a, a user (e.g., healthcare worker) selects one ormore enteral feeding products from the computed set of available enteralproducts which may be used to obtain a composition that is similar tothe ideal computed composition. Optionally, when protein content of theavailable enteral products is insufficient, and supplemental protein isrequired, the supplemental protein formulation may be selected asdescribed with reference to acts 119 and/or 120 of FIG. 1B.

At 14, the user inserts the selected enteral feeding product and/orsupplemental protein product into the enteral feeding system and clicksOK to approve the selection. The user may select the feeding mode asdescribed with reference to act 130 of FIG. 1B.

At 14 a the feeding tube is primed. At 18, the feeding rate iscalculated according to the best fit between the user selected enteralfeeding product and the ideal feeding rate of the ideal enteral feedingformulation.

At 13, the feeding pump delivers the user selected feeding product(s) topatient 10 via the feeding tube, according to the computed feeding rate.At 13 a, a pump control loop executed by the feeding pump may monitoredthe delivered enteral feeding, and adjust the actual feeding rateaccording to the computed feeding rate.

Feedback loop 302 is iterated, to dynamically compute the estimatedenergy expenditure and corresponding feeding rate, as described herein.

Reference is now made to FIGS. 6A-J, which is a sequence of exemplaryGUI images depicting an exemplary flow for implementing the method ofdynamically adjusting an enteral feeding device for controlling the feedrate according to an estimate of the energy expenditure computed basedon output of sensors and supplementing the feed formula with extraprotein (e.g., as described with reference to FIGS. 1A-B), in accordancewith some embodiments of the present invention.

FIG. 6A depicts a sequence of GUI images for determining the patientrest state based on an analysis of patient vital signs, for example, asdescribed with reference to feature 103 of FIGS. 1A-1B. GUI 602 depictsthat the patient is determined to be not at rest (i.e., unstable). GUI604 depicts that the patient is determined to be at rest. An initialfeeding rate and composition is set when the patient is determined to beat rest, for example, as described with reference to feature 102 ofFIGS. 1A-1B. GUI 606 depicts that the REE computation is starting. GUI608 depicts computation of the REE over a time interval. GUI 610 depictsthe resulting computed REE, shown as 1440 and 60 cc (cubiccentimeter)/hour.

FIG. 6B depicts a GUI image for setting clinical parameters of thepatient, including patient weight 612 and selecting from one or more ofthe following conditions 614: maintenance, stressed/MICU, Trauma/GeneralSurgery, Trauma/ICU, Burns, Cancer, and Obesity, for example, asdescribed with reference to feature 105 of FIGS. 1A-1B. The REE isautomatically computed based on the set clinical parameters, forexample, as described with reference to feature 106 of FIGS. 1A-1B.

In the depicted example, the patient weight 612 is set to 50 Kg, and noconditions 614 are selected. The REE 616 is computed as 1500, and 60cc/hour.

FIG. 6C depicts another setting of the GUI described with reference toFIG. 6B for another patient. In the depicted example, the patient weight612 is set to 85 Kg, and the condition 614 Trauma/ICU is selected. TheREE 616 is computed as 1800, and 75 cc/hour.

FIG. 6D depicts a GUI image that presents the best formula availablethat is closest to the computed target composition and/or target rate,i.e., optimal formula 618, for example, as described with reference tofeature 108 of FIGS. 1A-1B. In the depicted example, the Optimal FormulaOsmolite is selected, which includes 100% of the computed calories and85% of the protein based on the REE, at a rate of 75 cc/hour, forexample, as described with reference to feature 110 of FIGS. 1A-1B. Theformula is selected for continuous feeding. It is noted that the optimalformulas are selected to provide 100% of the computed required calories(or near 100%) irrespective of the protein requirements. The optimalformulas are selected based on the assumption that the remainingrequired protein will be met by adding a supplemental proteinformulation.

FIG. 6E depicts a GUI image that is presented when an analysisdetermines that the protein content of the selected optimal formulaOsmolite is insufficient, for example, as described with reference tofeature 119 of FIG. 1B. A list of supplemental protein formulas arepresented within the GUI for selection for addition to the selectedoptimal formula Osmolite, for example, as described with reference tofeature 120 of FIG. 1B. The list of supplemental protein formulas andrecommended amounts are automatically computed, for example, asdescribed with reference to the paragraph “Semi-automatically” withreference to feature 120 of FIG. 1B.

FIG. 6F depicts a GUI image of a selection of 45 grams of thesupplemental formula Gold Standard 100% for addition to the optimalformula Osmolite, for example, as described with reference to feature120 of FIG. 1B. FIG. 6G depicts a GUI image of a manual selection 620 ofthe type of formula and a manual selection of the quantity, for example,as described with reference to feature 110 of FIGS. 1A-1B, and/or asdescribed with reference to the paragraph “Manually by a user” withreference to feature 120 of FIG. 1B. In the depicted example, the usermanually selected to feed Osmolite at a rate of 75 cc/hour.

It is noted that the average feeding formula denoting available formulasthat are closes to the target composition, without supplemental proteinbeing added. Such average feeding formulas provide the closest possiblecalories and proteins to the patient.

FIG. 6H depicts the GUI image described with reference to FIG. 6G thatincludes a data entry field 622 for manually selecting the quantity forfeeding (i.e., other than the amounts available by clicking on thepresented quantity icons).

FIG. 6I depicts a GUI image for manually defining parameters of anintermittent feeding. Exemplary intermittent feeding parameters that maybe set include:

-   -   Frequency, for example, 2 hours, 3 hours, 4 hours, and 6 hours.    -   Duration, for example, 1 hour, 2 hours.    -   Taper up, for example, 5 minutes, 10 minutes, 15 minutes, and 20        minutes.    -   Taper down, for example, 5 minutes, 10 minutes, 15 minutes, and        20 minutes.

For example, as described with reference to feature 130 of FIG. 1B.

FIG. 6J depicts the GUI image described with reference to FIG. 6I, inwhich the following parameters are selected: Frequency of 4 hours,duration of 1 hour, taper up of 20 minutes. A timeline 624 maygraphically depict the feeding pattern during a 24 interval according tothe selected parameters. For example, solid portions of a first color ofthe timeline are indicative of time intervals during which enteringfeeding is taking place, the length of each solid portion of the firstcolor is according to the selected duration, solid portions of a secondcolor of the timeline are indicative of time intervals during whichenteral feeding is stopped, the length of each solid portion of thesecond color is according to the selected frequency less the selectedduration, mixed portions that represents a mixture of the first andsecond colors located before each solid portion of the first color areindicative of taper up and have a length according to the selected taperup time, and mixed portions located after each solid portion of thefirst color are indicative of taper down and have a length according tothe selected taper down time.

The descriptions of the various embodiments of the present inventionhave been presented for purposes of illustration, but are not intendedto be exhaustive or limited to the embodiments disclosed. Manymodifications and variations will be apparent to those of ordinary skillin the art without departing from the scope and spirit of the describedembodiments. The terminology used herein was chosen to best explain theprinciples of the embodiments, the practical application or technicalimprovement over technologies found in the marketplace, or to enableothers of ordinary skill in the art to understand the embodimentsdisclosed herein.

It is expected that during the life of a patent maturing from thisapplication many relevant enteral feeding controllers will be developedand the scope of the term enteral feeding controller is intended toinclude all such new technologies a priori.

As used herein the term “about” refers to ±10%.

The terms “comprises”, “comprising”, “includes”, “including”, “having”and their conjugates mean “including but not limited to”. This termencompasses the terms “consisting of” and “consisting essentially of”.

The phrase “consisting essentially of” means that the composition ormethod may include additional ingredients and/or steps, but only if theadditional ingredients and/or steps do not materially alter the basicand novel characteristics of the claimed composition or method.

As used herein, the singular form “a”, “an” and “the” include pluralreferences unless the context clearly dictates otherwise. For example,the term “a compound” or “at least one compound” may include a pluralityof compounds, including mixtures thereof.

The word “exemplary” is used herein to mean “serving as an example,instance or illustration”. Any embodiment described as “exemplary” isnot necessarily to be construed as preferred or advantageous over otherembodiments and/or to exclude the incorporation of features from otherembodiments.

The word “optionally” is used herein to mean “is provided in someembodiments and not provided in other embodiments”. Any particularembodiment of the invention may include a plurality of “optional”features unless such features conflict.

Throughout this application, various embodiments of this invention maybe presented in a range format. It should be understood that thedescription in range format is merely for convenience and brevity andshould not be construed as an inflexible limitation on the scope of theinvention. Accordingly, the description of a range should be consideredto have specifically disclosed all the possible subranges as well asindividual numerical values within that range. For example, descriptionof a range such as from 1 to 6 should be considered to have specificallydisclosed subranges such as from 1 to 3, from 1 to 4, from 1 to 5, from2 to 4, from 2 to 6, from 3 to 6 etc., as well as individual numberswithin that range, for example, 1, 2, 3, 4, 5, and 6. This appliesregardless of the breadth of the range.

Whenever a numerical range is indicated herein, it is meant to includeany cited numeral (fractional or integral) within the indicated range.The phrases “ranging/ranges between” a first indicate number and asecond indicate number and “ranging/ranges from” a first indicate number“to” a second indicate number are used herein interchangeably and aremeant to include the first and second indicated numbers and all thefractional and integral numerals therebetween.

It is appreciated that certain features of the invention, which are, forclarity, described in the context of separate embodiments, may also beprovided in combination in a single embodiment. Conversely, variousfeatures of the invention, which are, for brevity, described in thecontext of a single embodiment, may also be provided separately or inany suitable subcombination or as suitable in any other describedembodiment of the invention. Certain features described in the contextof various embodiments are not to be considered essential features ofthose embodiments, unless the embodiment is inoperative without thoseelements.

Although the invention has been described in conjunction with specificembodiments thereof, it is evident that many alternatives, modificationsand variations will be apparent to those skilled in the art.Accordingly, it is intended to embrace all such alternatives,modifications and variations that fall within the spirit and broad scopeof the appended claims.

It is the intent of the applicant(s) that all publications, patents andpatent applications referred to in this specification are to beincorporated in their entirety by reference into the specification, asif each individual publication, patent or patent application wasspecifically and individually noted when referenced that it is to beincorporated herein by reference. In addition, citation oridentification of any reference in this application shall not beconstrued as an admission that such reference is available as prior artto the present invention. To the extent that section headings are used,they should not be construed as necessarily limiting. In addition, anypriority document(s) of this application is/are hereby incorporatedherein by reference in its/their entirety.

What is claimed is:
 1. A computer-implemented method of adjusting enteral feeding of a patient by an enteral feeding controller, comprising: using at least one processor for executing a code for: receiving signals of at least one of a carbon dioxide sensor and an oxygen sensor, the at least one of carbon dioxide sensor and the oxygen sensor senses at least one of inspiration and expiration of the patient; receiving output of a flow sensor that senses at least one of inspiration and expiration of the patient; computing energy expenditure of the patient based on the output of the at least one of the carbon dioxide sensor and the oxygen sensor and the flow sensor; computing a target nutritional goal for the enteral feeding that provides 100% or near 100% of the computed energy expenditure of the patient irrespective of a predictive equation, wherein the target nutritional goal comprises caloric requirements and a target amount of protein; selecting a feeding formulation that provides the caloric requirements and provides less than a full amount of the target amount of protein; selecting a supplemental protein formulation that when added to the feeding formulation provides the full amount of the target amount of protein; generating instructions for adjustment, by an enteral feeding controller, for delivery of the feeding formulation and the supplemental protein formulation; and providing the generated instructions to the enteral feeding controller to deliver the feeding formulation and the supplemental protein formulation to the patient via an enteral feeding tube from at least one feed inlet of at least one feeding tube according to at least one of a feeding rate and a feeding composition defined by the generated instructions.
 2. The method of claim 1, further comprising computing a reduction in the feeding formulation in response to the selected supplemental protein formulation such that the feeding formulation with added selected supplemental protein formulation provides a full amount of the caloric requirements and the full amount of the target amount of protein.
 3. The computer implemented method of claim 1, further comprising: receiving signals of a nitrogen sensor that senses nitrogen in urine outputted by the patient, wherein the target amount of protein is computed according to the output of the nitrogen sensor.
 4. The computer implemented method of claim 1, further comprising iteratively computing the target amount of protein according to iterative measurements made by the nitrogen sensor, and iteratively generating the instructions for adjustment of delivery of the target amount of protein.
 5. The computer implemented method of claim 1, wherein an estimated amount of protein produced by the patient is computed based on the signals of the nitrogen sensor, and wherein the target amount of protein is computed at least for replacing the protein produced by the patient.
 6. The computer implemented method of claim 1, wherein the signals of the nitrogen sensor include a urine nitrogen measurement indicative of protein oxidation.
 7. The computer implemented method of claim 1, further comprising: when no nitrogen measurement is used, computing an estimate of the target amount of protein.
 8. The computer implemented method of claim 1, wherein the nitrogen sensor is associated with at least one of: a urinary catheter, a urine collection bag, urine flow device, and a urine output collection device.
 9. The computer implemented method of claim 1, further comprising computing a target amount of glucose of the target nutritional goal according to an analysis of the output of the at least one of the carbon dioxide sensor and the oxygen sensor and the flow sensor, wherein the instructions include instructions for adjustment, by the enteral feeding controller, for delivery of the target amount of glucose of the target nutritional goal.
 10. The computer implemented method of claim 1, further comprising computing a target amount of lipids of the target nutritional goal according to an analysis of the output of the at least one of the carbon dioxide sensor and the oxygen sensor and the flow sensor, wherein the instructions include instructions for adjustment, by the enteral feeding controller, for delivery of the target amount of lipids of the target nutritional goal.
 11. The computer implemented method of claim 1, wherein the target amount of protein comprises at least one of a weight and percentage of the target nutritional goal.
 12. The computer implemented method of claim 1, further comprising computing a target composition for reaching the target nutritional goal, wherein the target amount of protein is included in the target composition.
 13. The computer implemented method of claim 1, wherein the feeding controller includes a feeding selecting mechanism that alternatively switches between a protein tube through which the target amount of protein is provided, and a standard tube through which the feeding formulation is provided, each at a defined rate according to the generated instructions.
 14. The computer implemented method of claim 13, wherein the feed selecting mechanism controls which of the protein tube and the standard tube supplies its respective contents to a pump head for delivery to the patient via a tube outlet.
 15. The computer implemented method of claim 13, wherein a first and second set of generated instructions are for controlling the feeding selecting mechanism for selecting between the protein tube and the standard tube.
 16. The computer implemented method of claim 13, wherein the protein tube and the standard tube connect into the enteral feeding tube implemented as a single combined tube.
 17. The computer implemented method of claim 1, further comprising: receiving from a user via a graphical user interface (GUI), a selection of one icon indicative of one available supplemental protein formulation from a plurality of available formulations satisfying the target amount of protein, stored in a database storing records of different feeding formulas of supplemental protein, and presented within the GUI based on respective icons.
 18. A computing device for adjusting enteral feeding of a patient by an enteral feeding controller, comprising: at least one hardware processor executing a code for: receiving signals of at least one of a carbon dioxide sensor and an oxygen sensor, the at least one of carbon dioxide sensor and the oxygen sensor senses at least one of inspiration and expiration of the patient; receiving output of a flow sensor that senses at least one of inspiration and expiration of the patient; computing energy expenditure of the patient based on the output of the at least one of the carbon dioxide sensor and the oxygen sensor and the flow sensor; computing a target nutritional goal for the enteral feeding that provides 100% or near 100% of the computed energy expenditure of the patient irrespective of a predictive equation, wherein the target nutritional goal comprises caloric requirements and a target amount of protein; selecting a feeding formulation that provides the caloric requirements and provides less than a full amount of the target amount of protein; selecting a supplemental protein formulation that when added to the feeding formulation provides the full amount of the target amount of protein; generating instructions for adjustment, by an enteral feeding controller, for delivery of the feeding formulation and the supplemental protein formulation; and providing the generated instructions to the enteral feeding controller to deliver the feeding formulation and the supplemental protein formulation to the patient via an enteral feeding tube from at least one feed inlet of at least one feeding tube according to at least one of a feeding rate and a feeding composition defined by the generated instructions.
 19. A computer program product for adjusting enteral feeding of a patient by an enteral feeding controller, which, when executed by a processor, cause the processor to perform: receiving signals of at least one of a carbon dioxide sensor and an oxygen sensor, the at least one of carbon dioxide sensor and the oxygen sensor senses at least one of inspiration and expiration of the patient; receiving output of a flow sensor that senses at least one of inspiration and expiration of the patient; computing energy expenditure of the patient based on the output of the at least one of the carbon dioxide sensor and the oxygen sensor and the flow sensor; computing a target nutritional goal for the enteral feeding that provides 100% or near 100% of the computed energy expenditure of the patient irrespective of a predictive equation, wherein the target nutritional goal comprises caloric requirements and a target amount of protein; selecting a feeding formulation that provides the caloric requirements and provides less than a full amount of the target amount of protein; selecting a supplemental protein formulation that when added to the feeding formulation provides the full amount of the target amount of protein; generating instructions for adjustment, by an enteral feeding controller, for delivery of the feeding formulation and the supplemental protein formulation; and providing the generated instructions to the enteral feeding controller to deliver the feeding formulation and the supplemental protein formulation to the patient via an enteral feeding tube from at least one feed inlet of at least one feeding tube according to at least one of a feeding rate and a feeding composition defined by the generated instructions. 